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Background Neglected tropical diseases are responsible for considerable morbidity and mortality in low-income populations. International efforts have reduced their global burden, but transmission is persistent and case-finding-based interventions rarely target asymptomatic individuals. Methods We develop a generic mathematical modeling framework for analyzing the dynamics of visceral leishmaniasis in the Indian sub-continent (VL), gambiense sleeping sickness (gHAT), and Chagas disease and use it to assess the possible contribution of asymptomatics who later develop disease (pre-symptomatics) and those who do not (non-symptomatics) to the maintenance of infection. Plausible interventions, including active screening, vector control, and reduced time to detection, are simulated for the three diseases. Results We found that the high asymptomatic contribution to transmission for Chagas and gHAT and the apparently high basic reproductive number of VL may undermine long-term control. However, the ability to treat some asymptomatics for Chagas and gHAT should make them more controllable, albeit over relatively long time periods due to the slow dynamics of these diseases. For VL, the toxicity of available therapeutics means the asymptomatic population cannot currently be treated, but combining treatment of symptomatics and vector control could yield a quick reduction in transmission. Conclusions Despite the uncertainty in natural history, it appears there is already a relatively good toolbox of interventions to eliminate gHAT, and it is likely that Chagas will need improvements to diagnostics and their use to better target pre-symptomatics. The situation for VL is less clear, and model predictions could be improved by additional empirical data. However, interventions may have to improve to successfully eliminate this disease. [ABSTRACT FROM AUTHOR]

Background: Recurring COVID-19 waves highlight the need for tools able to quantify transmission risk, and identify geographical areas at risk of outbreaks. Local outbreak risk depends on complex immunity patterns resulting from previous infections, vaccination, waning and immune escape, alongside other factors (population density, social contact patterns). Immunity patterns are spatially and demographically heterogeneous, and are challenging to capture in country-level forecast models. Methods: We used a spatiotemporal regression model to forecast subnational case and death counts and applied it to three EU countries as test cases: France, Czechia, and Italy. Cases in local regions arise from importations or local transmission. Our model produces age-stratified forecasts given age-stratified data, and links reported case counts to routinely collected covariates (e.g. test number, vaccine coverage). We assessed the predictive performance of our model up to four weeks ahead using proper scoring rules and compared it to the European COVID-19 Forecast Hub ensemble model. Using simulations, we evaluated the impact of variations in transmission on the forecasts. We developed an open-source RShiny App to visualise the forecasts and scenarios. Results: At a national level, the median relative difference between our median weekly case forecasts and the data up to four weeks ahead was 25% (IQR: 12–50%) over the prediction period. The accuracy decreased as the forecast horizon increased (on average 24% increase in the median ranked probability score per added week), while the accuracy of death forecasts was more stable. Beyond two weeks, the model generated a narrow range of likely transmission dynamics. The median national case forecasts showed similar accuracy to forecasts from the European COVID-19 Forecast Hub ensemble model, but the prediction interval was narrower in our model. Generating forecasts under alternative transmission scenarios was therefore key to capturing the range of possible short-term transmission dynamics. Discussion: Our model captures changes in local COVID-19 outbreak dynamics, and enables quantification of short-term transmission risk at a subnational level. The outputs of the model improve our ability to identify areas where outbreaks are most likely, and are available to a wide range of public health professionals through the Shiny App we developed. [ABSTRACT FROM AUTHOR]

A key public health question during any disease outbreak when limited vaccine is available is who should be prioritized for early vaccination. Most vaccine prioritization analyses only consider variation in risk of infection and death by a single risk factor, such as age. We provide a more granular approach with stratification by demographics, risk factors, and location. We use this approach to compare the impact of different COVID-19 vaccine prioritization strategies on COVID-19 cases, deaths and disability-adjusted life years (DALYs) over the first 6 months of vaccine rollout, using California as a case example. We estimate the proportion of cases, deaths and DALYs averted relative to no vaccination for strategies prioritizing vaccination by a single risk factor and by multiple risk factors (e.g. age, location). When targeting by a single risk factor, we find that age-based targeting averts the most deaths (62% for 5 million individuals vaccinated) and DALYs (38%) and targeting essential workers averts the least deaths (31%) and DALYs (24%) over the first 6 months of rollout. However, targeting by two or more risk factors simultaneously averts up to 40% more DALYs. Our findings highlight the potential value of multiple-risk-factor targeting of vaccination against COVID-19 and other infectious diseases, but must be balanced with feasibility for policy. [ABSTRACT FROM AUTHOR]

Background: COVID-19 outbreaks have occurred in homeless shelters across the US, highlighting an urgent need to identify the most effective infection control strategy to prevent future outbreaks.Methods: We developed a microsimulation model of SARS-CoV-2 transmission in a homeless shelter and calibrated it to data from cross-sectional polymerase chain reaction (PCR) surveys conducted during COVID-19 outbreaks in five homeless shelters in three US cities from March 28 to April 10, 2020. We estimated the probability of averting a COVID-19 outbreak when an exposed individual is introduced into a representative homeless shelter of 250 residents and 50 staff over 30 days under different infection control strategies, including daily symptom-based screening, twice-weekly PCR testing, and universal mask wearing.Results: The proportion of PCR-positive residents and staff at the shelters with observed outbreaks ranged from 2.6 to 51.6%, which translated to the basic reproduction number (R0) estimates of 2.9-6.2. With moderate community incidence (~ 30 confirmed cases/1,000,000 people/day), the estimated probabilities of averting an outbreak in a low-risk (R0 = 1.5), moderate-risk (R0 = 2.9), and high-risk (R0 = 6.2) shelter were respectively 0.35, 0.13, and 0.04 for daily symptom-based screening; 0.53, 0.20, and 0.09 for twice-weekly PCR testing; 0.62, 0.27, and 0.08 for universal masking; and 0.74, 0.42, and 0.19 for these strategies in combination. The probability of averting an outbreak diminished with higher transmissibility (R0) within the simulated shelter and increasing incidence in the local community.Conclusions: In high-risk homeless shelter environments and locations with high community incidence of COVID-19, even intensive infection control strategies (incorporating daily symptom screening, frequent PCR testing, and universal mask wearing) are unlikely to prevent outbreaks, suggesting a need for non-congregate housing arrangements for people experiencing homelessness. In lower-risk environments, combined interventions should be employed to reduce outbreak risk. [ABSTRACT FROM AUTHOR]

Understanding of spatiotemporal transmission of infectious diseases has improved significantly in recent years. Advances in Bayesian inference methods for individual-level geo-located epidemiological data have enabled reconstruction of transmission trees and quantification of disease spread in space and time, while accounting for uncertainty in missing data. However, these methods have rarely been applied to endemic diseases or ones in which asymptomatic infection plays a role, for which additional estimation methods are required. Here, we develop such methods to analyze longitudinal incidence data on visceral leishmaniasis (VL) and its sequela, post-kala-azar dermal leishmaniasis (PKDL), in a highly endemic community in Bangladesh. Incorporating recent data on VL and PKDL infectiousness, we show that while VL cases drive transmission when incidence is high, the contribution of PKDL increases significantly as VL incidence declines (reaching 55% in this setting). Transmission is highly focal: 85% of mean distances from inferred infectors to their secondary VL cases were <300 m, and estimated average times from infector onset to secondary case infection were <4 mo for 88% of VL infectors, but up to 2.9 y for PKDL infectors. Estimated numbers of secondary cases per VL and PKDL case varied from 0 to 6 and were strongly correlated with the infector's duration of symptoms. Counterfactual simulations suggest that prevention of PKDL could have reduced overall VL incidence by up to 25%. These results highlight the need for prompt detection and treatment of PKDL to achieve VL elimination in the Indian subcontinent and provide quantitative estimates to guide spatiotemporally targeted interventions against VL. [ABSTRACT FROM AUTHOR]

Background: The elimination programme for visceral leishmaniasis (VL) in India has seen great progress, with total cases decreasing by over 80% since 2010 and many blocks now reporting zero cases from year to year. Prompt diagnosis and treatment is critical to continue progress and avoid epidemics in the increasingly susceptible population. Short-term forecasts could be used to highlight anomalies in incidence and support health service logistics. The model which best fits the data is not necessarily most useful for prediction, yet little empirical work has been done to investigate the balance between fit and predictive performance. Methodology/Principal findings: We developed statistical models of monthly VL case counts at block level. By evaluating a set of randomly-generated models, we found that fit and one-month-ahead prediction were strongly correlated and that rolling updates to model parameters as data accrued were not crucial for accurate prediction. The final model incorporated auto-regression over four months, spatial correlation between neighbouring blocks, and seasonality. Ninety-four percent of 10-90% prediction intervals from this model captured the observed count during a 24-month test period. Comparison of one-, three- and four-month-ahead predictions from the final model fit demonstrated that a longer time horizon yielded only a small sacrifice in predictive power for the vast majority of blocks. Conclusions/Significance: The model developed is informed by routinely-collected surveillance data as it accumulates, and predictions are sufficiently accurate and precise to be useful. Such forecasts could, for example, be used to guide stock requirements for rapid diagnostic tests and drugs. More comprehensive data on factors thought to influence geographic variation in VL burden could be incorporated, and might better explain the heterogeneity between blocks and improve uniformity of predictive performance. Integration of the approach in the management of the VL programme would be an important step to ensuring continued successful control. Author summary: This paper demonstrates a statistical modelling approach for forecasting of monthly visceral leishmaniasis (VL) incidence at block level in India, which could be used to tailor control efforts according to local estimates and monitor deviations from the currently decreasing trend. By fitting a variety of models to four years of historical data and assessing predictions within a further 24-month test period, we found that the model which best fit the observed data also showed the best predictive performance, and predictive accuracy was maintained when making rolling predictions up to four months ahead of the observed data. Since there is a two-month delay between reporting and processing of the data, predictive power more than three months ahead of current data is crucial to make forecasts which can feasibly be acted upon. Some heterogeneity remains in predictive power across the study region which could potentially be improved using unit-specific data on factors believed to be associated with reported VL incidence (e.g. age distribution, socio-economic status and climate). [ABSTRACT FROM AUTHOR]

Background: Age patterns in asymptomatic and symptomatic infection with Leishmania donovani, the causative agent of visceral leishmaniasis (VL) in the Indian subcontinent (ISC), are currently poorly understood. Age-stratified serology and infection incidence have been used to assess transmission levels of other diseases, which suggests that they may also be of use for monitoring and targeting control programmes to achieve elimination of VL and should be included in VL transmission dynamic models. We therefore analysed available age-stratified data on both disease incidence and prevalence of immune markers with the aim of collating the currently available data, estimating rates of infection, and informing modelling and future data collection. Methodology/Principal findings: A systematic literature search yielded 13 infection prevalence and 7 VL incidence studies meeting the inclusion criteria. Statistical tests were performed to identify trends by age, and according to diagnostic cut-off. Simple reversible catalytic models with age-independent and age-dependent infection rates were fitted to the prevalence data to estimate infection and reversion rates, and to test different hypotheses about the origin of variation in these rates. Most of the studies showed an increase in infection prevalence with age: from ≲10% seroprevalence (<20% Leishmanin skin test (LST) positivity) for 0-10-year-olds to >10% seroprevalence (>20% LST-positivity) for 30-40-year-olds, but overall prevalence varied considerably between studies. VL incidence was lower amongst 0-5-year-olds than older age groups in most studies; most showing a peak in incidence between ages 5 and 20. The age-independent catalytic model provided the best overall fit to the infection prevalence data, but the estimated rates for the less parsimonious age-dependent model were much closer to estimates from longitudinal studies, suggesting that infection rates may increase with age. Conclusions/Significance: Age patterns in asymptomatic infection prevalence and VL incidence in the ISC vary considerably with geographical location and time period. The increase in infection prevalence with age and peaked age-VL-incidence distribution may be due to lower exposure to infectious sandfly bites in young children, but also suggest that acquired immunity to the parasite increases with age. However, poor standardisation of serological tests makes it difficult to compare data from different studies and draw firm conclusions about drivers of variation in observed age patterns. [ABSTRACT FROM AUTHOR]

Background: Visceral leishmaniasis (VL) is characterised by a high degree of spatial clustering at all scales, and this feature remains even with successful control measures. VL is targeted for elimination as a public health problem in the Indian subcontinent by 2020, and incidence has been falling rapidly since 2011. Current control is based on early diagnosis and treatment of clinical cases, and blanket indoor residual spraying of insecticide (IRS) in endemic villages to kill the sandfly vectors. Spatially targeting active case detection and/or IRS to higher risk areas would greatly reduce costs of control, but its effectiveness as a control strategy is unknown. The effectiveness depends on two key unknowns: how quickly transmission risk decreases with distance from a VL case and how much asymptomatically infected individuals contribute to transmission. Methodology/Principal findings: To estimate these key parameters, a spatiotemporal transmission model for VL was developed and fitted to geo-located epidemiological data on 2494 individuals from a highly endemic village in Mymensingh, Bangladesh. A Bayesian inference framework that could account for the unknown infection times of the VL cases, and missing symptom onset and recovery times, was developed to perform the parameter estimation. The parameter estimates obtained suggest that, in a highly endemic setting, VL risk decreases relatively quickly with distance from a case—halving within 90m—and that VL cases contribute significantly more to transmission than asymptomatic individuals. Conclusions/Significance: These results suggest that spatially-targeted interventions may be effective for limiting transmission. However, the extent to which spatial transmission patterns and the asymptomatic contribution vary with VL endemicity and over time is uncertain. In any event, interventions would need to be performed promptly and in a large radius (≥300m) around a new case to reduce transmission risk. [ABSTRACT FROM AUTHOR]

Systemic insecticides in dogs have been suggested as a public health intervention to prevent human cases of Zoonotic Visceral Leishmaniasis (ZVL). But, currently there are no systemic insecticides for dogs registered against zoo-anthropophilic pool blood feeding phlebotomine flies. We predict the impact of community-wide use of systemic insecticide in dog populations as a public health measure to control transmission of Leishmania infantum to humans using a mathematical model. We developed a Susceptible-Exposed-Infected (SEI) compartmental model to describe L. infantum transmission dynamics in dogs, with a vectorial capacity term to represent transmission between L. infantum-hosting dogs via phlebotomine flies. For Infected (I) dogs two levels of infectiousness were modelled, high infectiousness and low infectiousness. Human incidence was estimated through its relationship to infection in the dog population. We evaluated outcomes from a wide range of scenarios comprising different combinations of initial insecticide efficacy, duration of insecticide efficacy over time, and proportion of the dog population treated (60%, 70% & 80%). The same reduction in human infection incidence can be achieved via different combinations of insecticide efficacy, duration and dog coverage. For example, a systemic insecticide with an initial efficacy of 80% and 6 months above 65% efficacy would require treating at least 70% of the dogs to reduce the human infection incidence by 50%. Sensitivity analysis showed that the model outcome was most sensitive to baseline values of phlebotomine fly daily survival rate and insecticide coverage. Community-wide use of systemic insecticides applied to the “L. infantum canine reservoir” can significantly reduce human incidence of L. infantum infection. The results of this mathematical model can help defining the insecticide target product profile and how the insecticide should be applied to maximise effectiveness. [ABSTRACT FROM AUTHOR]

Background. Visceral leishmaniasis (VL) has been targeted by the World Health Organization (WHO) and 5 countries in the Indian subcontinent for elimination as a public health problem. To achieve this target, the WHO has developed guidelines consisting of 4 phases of different levels of interventions, based on vector control through indoor residual spraying of insecticide (IRS) and active case detection (ACD). Mathematical transmission models of VL are increasingly used for planning and assessing the efficacy of interventions and evaluating the intensity and timescale required to achieve the elimination target. Methods. This paper draws together the key policy-relevant conclusions from recent transmission modeling of VL, and presents new predictions for VL incidence under the interventions recommended by the WHO using the latest transmission models. Results. The model predictions suggest that the current WHO guidelines should be sufficient to reach the elimination target in areas that had medium VL endemicities (up to 5 VL cases per 10 000 population per year) prior to the start of interventions. However, additional interventions, such as extending the WHO attack phase (intensive IRS and ACD), may be required to bring forward elimination in regions with high precontrol endemicities, depending on the relative infectiousness of different disease stages. Conclusions. The potential hurdle that asymptomatic and, in particular, post-kala-azar dermal leishmaniasis cases may pose to reaching and sustaining the target needs to be addressed. As VL incidence decreases, the pool of immunologically naive individuals will grow, creating the potential for new outbreaks. [ABSTRACT FROM AUTHOR]

Background: Visceral leishmaniasis (VL) has been targeted by the WHO for elimination as a public health problem (< 1 case/10,000 people/year) in the Indian sub-continent (ISC) by 2020. Bihar State in India, which accounts for the majority of cases in the ISC, remains a major target for this elimination effort. However, there is considerable spatial, temporal and sub-population variation in occurrence of the disease and the pathway to care, which is largely unexplored and a threat to achieving the target. Methods: Data from 6081 suspected VL patients who reported being clinically diagnosed during 2012-2013 across eight districts in Bihar were analysed. Graphical comparisons and Chi-square tests were used to determine differences in the burden of identified cases by season, district, age and sex. Log-linear regression models were fitted to onset (of symptoms)-to-diagnosis and onset-to-treatment waiting times to estimate their associations with age, sex, district and various socio-economic factors (SEFs). Logistic regression models were used to identify factors associated with mortality. Results: Comparisons of VL caseloads suggested an annual cycle peaking in January-March. A 17-fold variation in the burden of identified cases across districts and under-representation of young children (0-5 years) relative to age-specific populations in Bihar were observed. Women accounted for a significantly lower proportion of the reported cases than men (41 vs 59%, P < 0.0001). Age, district of residence, house wall materials, caste, treatment cost, travelling for diagnosis and the number of treatments for symptoms before diagnosis were identified as correlates of waiting times. Mortality was associated with age, district of residence, onset-to-treatment waiting time, treatment duration, cattle ownership and cost of diagnosis. Conclusions: The distribution of VL in Bihar is highly heterogeneous, and reported caseloads and associated mortality vary significantly across different districts, posing different challenges to the elimination campaign. Socio-economic factors are important correlates of these differences, suggesting that elimination will require tailoring to population and sub-population circumstances. [ABSTRACT FROM AUTHOR]

Background: Visceral leishmaniasis has been targeted for elimination as a public health problem (less than 1 case per 10,000 people per year) in the Indian sub-continent by 2017. However, there is still a high degree of uncertainty about the natural history of the disease, in particular about the duration of asymptomatic infection and the proportion of asymptomatically infected individuals that develop clinical visceral leishmaniasis. Quantifying these aspects of the disease is key for guiding efforts to eliminate visceral leishmaniasis and maintaining elimination once it is reached. Methods: Data from a detailed epidemiological study in Bangladesh in 2002-2004 was analysed to estimate key epidemiological parameters. The role of diagnostics in determining the probability and rate of progression to clinical disease was estimated by fitting Cox proportional hazards models. A multi-state Markov model of the natural history of visceral leishmaniasis was fitted to the data to estimate the asymptomatic infection period and the proportion of asymptomatic individuals going on to develop clinical symptoms. Results: At the time of the study, individuals were taking several months to be diagnosed with visceral leishmaniasis, leading to many opportunities for ongoing transmission. The probability of progression to clinical disease was strongly associated with initial seropositivity and even more strongly with seroconversion, with most clinical symptoms developing within a year. The estimated average durations of asymptomatic infection and symptomatic infection for our model of the natural history are 147 days (95 % CI 130-166) and 140 days (95 % CI 123-160), respectively, and are significantly longer than previously reported estimates. We estimate from the data that 14.7 % (95 % CI 12.6-20.0 %) of asymptomatic individuals develop clinical symptoms-a greater proportion than previously estimated. Conclusions: Extended periods of asymptomatic infection could be important for visceral leishmaniasis transmission, but this depends critically on the relative infectivity of asymptomatic and symptomatic individuals to sandflies. These estimates could be informed by similar analysis of other datasets. Our results highlight the importance of reducing times from onset of symptoms to diagnosis and treatment to reduce opportunities for transmission. [ABSTRACT FROM AUTHOR]

The need for efficient and controlled expansion of cell populations is paramount in tissue engineering. Hollow fibre bioreactors (HFBs) have the potential to meet this need, but only with improved understanding of how operating conditions and cell seeding strategy affect cell proliferation in the bioreactor. This study is designed to assess the effects of two key operating parameters (the flow rate of culture medium into the fibre lumen and the fluid pressure imposed at the lumen outlet), together with the cell seeding distribution, on cell population growth in a single-fibre HFB. This is achieved using mathematical modelling and numerical methods to simulate the growth of cell aggregates along the outer surface of the fibre in response to the local oxygen concentration and fluid shear stress. The oxygen delivery to the cell aggregates and the fluid shear stress increase as the flow rate and pressure imposed at the lumen outlet are increased. Although the increased oxygen delivery promotes growth, the higher fluid shear stress can lead to cell death. For a given cell type and initial aggregate distribution, the operating parameters that give the most rapid overall growth can be identified from simulations. For example, when aggregates of rat cardiomyocytes that can tolerate shear stresses of up to are evenly distributed along the fibre, the inlet flow rate and outlet pressure that maximise the overall growth rate are predicted to be in the ranges to (equivalent to to ) and to (or 15.6 psi to 15.7 psi) respectively. The combined effects of the seeding distribution and flow on the growth are also investigated and the optimal conditions for growth found to depend on the shear tolerance and oxygen demands of the cells. [ABSTRACT FROM AUTHOR]

A correction is presented to the article "Estimating the efficacy of community-wide use of systemic insecticides in dogs to control zoonotic visceral leishmaniasis: A modelling study in a Brazilian scenario" which was published in the 28 May, 2019 issue of the periodical.

Introduction: Visceral leishmaniasis (VL), a neglected tropical disease that causes substantial morbidity and mortality, is a serious health problem in Ethiopia. Infections are caused by Leishmania (L.) donovani parasites. Most individuals remain asymptomatic, but some develop VL, which is generally fatal if not treated. We identified the area of Metema-Humera in Northwest Ethiopia as a setting in which we could follow migrant workers when they arrived in an endemic area. The demographic characteristics of this population and factors associated with their risk of asymptomatic infection are poorly characterised. Methods: We divided our cohort into individuals who visited this area for the first time (first comers, FC) and those who had already been in this area (repeat comers, RC). We followed them from the beginning (Time 1, T1) to the end of the agricultural season (Time 2, T2), performing tests for sand fly bite exposure (anti-sand fly saliva antibody ELISA) and serology for Leishmania infection (rK39 rapid diagnostic test and the direct agglutination test) at each time point and collecting information on risk factors for infection. Results: Our results show that most migrant workers come from non-endemic areas, are male, young (median age of 20 years) and are farmers or students. At T1, >80% of them had been already exposed to sand fly bites, as shown by the presence of anti-saliva antibodies. However, due to seasonality of sand flies there was no difference in exposure between FC and RC, or between T1 and T2. The serology data showed that at T1, but not at T2, a significantly higher proportion of RC were asymptomatic. Furthermore, 28.6% of FC became asymptomatic between T1 and T2. Over the duration of this study, one FC and one RC developed VL. In multivariable logistic regression of asymptomatic infection at T1, only age and the number of visits to Metema/Humera were significantly associated with asymptomatic infection. Conclusion: A better understanding of the dynamics of parasite transmission and the risk factors associated with the development of asymptomatic infections and potentially VL will be essential for the development of new strategies to prevent leishmaniasis. [ABSTRACT FROM AUTHOR]

The emergence of successive Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) during 2020 to 2022, each exhibiting increased epidemic growth relative to earlier circulating variants, has created a need to understand the drivers of such growth. However, both pathogen biology and changing host characteristics—such as varying levels of immunity—can combine to influence replication and transmission of SARS-CoV-2 within and between hosts. Disentangling the role of variant and host in individual-level viral shedding of VOCs is essential to inform Coronavirus Disease 2019 (COVID-19) planning and response and interpret past epidemic trends. Using data from a prospective observational cohort study of healthy adult volunteers undergoing weekly occupational health PCR screening, we developed a Bayesian hierarchical model to reconstruct individual-level viral kinetics and estimate how different factors shaped viral dynamics, measured by PCR cycle threshold (Ct) values over time. Jointly accounting for both interindividual variation in Ct values and complex host characteristics—such as vaccination status, exposure history, and age—we found that age and number of prior exposures had a strong influence on peak viral replication. Older individuals and those who had at least 5 prior antigen exposures to vaccination and/or infection typically had much lower levels of shedding. Moreover, we found evidence of a correlation between the speed of early shedding and duration of incubation period when comparing different VOCs and age groups. Our findings illustrate the value of linking information on participant characteristics, symptom profile and infecting variant with prospective PCR sampling, and the importance of accounting for increasingly complex population exposure landscapes when analysing the viral kinetics of VOCs. Trial Registration: The Legacy study is a prospective observational cohort study of healthy adult volunteers undergoing weekly occupational health PCR screening for SARS-CoV-2 at University College London Hospitals or at the Francis Crick Institute (NCT04750356) (22,23). The Legacy study was approved by London Camden and Kings Cross Health Research Authority Research and Ethics committee (IRAS number 286469). The Legacy study was approved by London Camden and Kings Cross Health Research Authority Research and Ethics committee (IRAS number 286469) and is sponsored by University College London Hospitals. Written consent was given by all participants. The emergence of successive SARS-CoV-2 variants of concern during 2020-22 created a need to understand the drivers of such growth. This study uses a Bayesian model to reveal how a set of key covariates (the infecting variant, symptom status, age and number of prior exposures) affect viral kinetics at both individual and population levels. [ABSTRACT FROM AUTHOR]

Routine asymptomatic testing strategies for COVID-19 have been proposed to prevent outbreaks in high-risk healthcare environments. We used simulation modeling to evaluate the optimal frequency of viral testing. We found that routine testing substantially reduces risk of outbreaks, but may need to be as frequent as twice weekly. [ABSTRACT FROM AUTHOR]

This study uses US Immigration and Customs Enforcement (ICE) Health Service Corps data to describe incident cases and outbreaks of influenza, varicella, and mumps in 22 US ICE detention centers between 2017 and March 2020. [ABSTRACT FROM AUTHOR]

Background: Forecasting healthcare demand is essential in epidemic settings, both to inform situational awareness and facilitate resource planning. Ideally, forecasts should be robust across time and locations. During the COVID-19 pandemic in England, it is an ongoing concern that demand for hospital care for COVID-19 patients in England will exceed available resources.Methods: We made weekly forecasts of daily COVID-19 hospital admissions for National Health Service (NHS) Trusts in England between August 2020 and April 2021 using three disease-agnostic forecasting models: a mean ensemble of autoregressive time series models, a linear regression model with 7-day-lagged local cases as a predictor, and a scaled convolution of local cases and a delay distribution. We compared their point and probabilistic accuracy to a mean-ensemble of them all and to a simple baseline model of no change from the last day of admissions. We measured predictive performance using the weighted interval score (WIS) and considered how this changed in different scenarios (the length of the predictive horizon, the date on which the forecast was made, and by location), as well as how much admissions forecasts improved when future cases were known.Results: All models outperformed the baseline in the majority of scenarios. Forecasting accuracy varied by forecast date and location, depending on the trajectory of the outbreak, and all individual models had instances where they were the top- or bottom-ranked model. Forecasts produced by the mean-ensemble were both the most accurate and most consistently accurate forecasts amongst all the models considered. Forecasting accuracy was improved when using future observed, rather than forecast, cases, especially at longer forecast horizons.Conclusions: Assuming no change in current admissions is rarely better than including at least a trend. Using confirmed COVID-19 cases as a predictor can improve admissions forecasts in some scenarios, but this is variable and depends on the ability to make consistently good case forecasts. However, ensemble forecasts can make forecasts that make consistently more accurate forecasts across time and locations. Given minimal requirements on data and computation, our admissions forecasting ensemble could be used to anticipate healthcare needs in future epidemic or pandemic settings. [ABSTRACT FROM AUTHOR]

Despite a large amount of in vitro data, the dynamics of airway smooth muscle (ASM) mass increase in the airways of patients with asthma is not well understood. Here, we present a novel mathematical model that describes qualitatively the growth dynamics of ASM cells over short and long terms in the normal and inflammatory environments typically observed in asthma. The degree of ASM accumulation can be explained by an increase in the rate at which ASM cells switch between non-proliferative and proliferative states, driven by episodic inflammatory events. Our model explores the idea that remodelling due to ASM hyperplasia increases with the frequency and magnitude of these inflammatory events, relative to certain sensitivity thresholds. It highlights the importance of inflammation resolution speed by showing that when resolution is slow, even a series of small exacerbation events can result in significant remodelling, which persists after the inflammatory episodes. In addition, we demonstrate how the uncertainty in long-term outcome may be quantified and used to design an optimal low-risk individual anti-proliferative treatment strategy. The model shows that the rate of clearance of ASM proliferation and recruitment factors after an acute inflammatory event is a potentially important, and hitherto unrecognised, target for anti-remodelling therapy in asthma. It also suggests new ways of quantifying inflammation severity that could improve prediction of the extent of ASM accumulation. This ASM growth model should prove useful for designing new experiments or as a building block of more detailed multi-cellular tissue-level models. [ABSTRACT FROM AUTHOR]

Background: With visceral leishmaniasis (VL) incidence at its lowest level since the 1960s, increasing attention has turned to early detection and investigation of outbreaks. Methods: Outbreak investigations were triggered by recognition of case clusters in the VL surveillance system established for the elimination program. Investigations included ascertainment of all VL cases by date of fever onset, household mapping and structured collection of risk factor data. Results: VL outbreaks were investigated in 13 villages in 10 blocks of 7 districts. Data were collected for 20,670 individuals, of whom 272 were diagnosed with VL between 2012 and 2019. Risk was significantly higher among 10–19 year-olds and adults 35 or older compared to children younger than 10 years. Outbreak confirmation triggered vector control activities and heightened surveillance. VL cases strongly clustered in tolas (hamlets within villages) in which > 66% of residents self-identified as scheduled caste or scheduled tribe (SC/ST); 79.8% of VL cases occurred in SC/ST tolas whereas only 24.2% of the population resided in them. Other significant risk factors included being an unskilled non-agricultural laborer, migration for work in a brick kiln, living in a kuccha (mud brick) house, household crowding, habitually sleeping outside or on the ground, and open defecation. Conclusions: Our data highlight the importance of sensitive surveillance with triggers for case cluster detection and rapid, careful outbreak investigations to better respond to ongoing and new transmission. The strong association with SC/ST tolas suggests that efforts should focus on enhanced surveillance in these disadvantaged communities. [ABSTRACT FROM AUTHOR]

Background: With visceral leishmaniasis (VL) incidence at its lowest level since the 1960s, increasing attention has turned to early detection and investigation of outbreaks. Methods: Outbreak investigations were triggered by recognition of case clusters in the VL surveillance system established for the elimination program. Investigations included ascertainment of all VL cases by date of fever onset, household mapping and structured collection of risk factor data. Results: VL outbreaks were investigated in 13 villages in 10 blocks of 7 districts. Data were collected for 20,670 individuals, of whom 272 were diagnosed with VL between 2012 and 2019. Risk was significantly higher among 10–19 year-olds and adults 35 or older compared to children younger than 10 years. Outbreak confirmation triggered vector control activities and heightened surveillance. VL cases strongly clustered in tolas (hamlets within villages) in which > 66% of residents self-identified as scheduled caste or scheduled tribe (SC/ST); 79.8% of VL cases occurred in SC/ST tolas whereas only 24.2% of the population resided in them. Other significant risk factors included being an unskilled non-agricultural laborer, migration for work in a brick kiln, living in a kuccha (mud brick) house, household crowding, habitually sleeping outside or on the ground, and open defecation. Conclusions: Our data highlight the importance of sensitive surveillance with triggers for case cluster detection and rapid, careful outbreak investigations to better respond to ongoing and new transmission. The strong association with SC/ST tolas suggests that efforts should focus on enhanced surveillance in these disadvantaged communities. [ABSTRACT FROM AUTHOR]

Background: Routine viral testing strategies for SARS-CoV-2 infection might facilitate safe airline travel during the COVID-19 pandemic and mitigate global spread of the virus. However, the effectiveness of these test-and-travel strategies to reduce passenger risk of SARS-CoV-2 infection and population-level transmission remains unknown.Methods: In this simulation study, we developed a microsimulation of SARS-CoV-2 transmission in a cohort of 100 000 US domestic airline travellers using publicly available data on COVID-19 clinical cases and published natural history parameters to assign individuals one of five health states of susceptible to infection, latent period, early infection, late infection, or recovered. We estimated a per-day risk of infection with SARS-CoV-2 corresponding to a daily incidence of 150 infections per 100 000 people. We assessed five testing strategies: (1) anterior nasal PCR test within 3 days of departure, (2) PCR within 3 days of departure and 5 days after arrival, (3) rapid antigen test on the day of travel (assuming 90% of the sensitivity of PCR during active infection), (4) rapid antigen test on the day of travel and PCR test 5 days after arrival, and (5) PCR test 5 days after arrival. Strategies 2 and 4 included a 5-day quarantine after arrival. The travel period was defined as 3 days before travel to 2 weeks after travel. Under each scenario, individuals who tested positive before travel were not permitted to travel. The primary study outcome was cumulative number of infectious days in the cohort over the travel period without isolation or quarantine (population-level transmission risk), and the key secondary outcome was the number of infectious people detected on the day of travel (passenger risk of infection).Findings: We estimated that in a cohort of 100 000 airline travellers, in a scenario with no testing or screening, there would be 8357 (95% uncertainty interval 6144-12831) infectious days with 649 (505-950) actively infectious passengers on the day of travel. The pre-travel PCR test reduced the number of infectious days from 8357 to 5401 (3917-8677), a reduction of 36% (29-41) compared with the base case, and identified 569 (88% [76-92]) of 649 actively infectious travellers on the day of flight; the addition of post-travel quarantine and PCR reduced the number of infectious days to 2520 days (1849-4158), a reduction of 70% (64-75) compared with the base case. The rapid antigen test on the day of travel reduced the number of infectious days to 5674 (4126-9081), a reduction of 32% (26-38) compared with the base case, and identified 560 (86% [83-89]) actively infectious travellers; the addition of post-travel quarantine and PCR reduced the number of infectious days to 3124 (2356-495), a reduction of 63% (58-66) compared with the base case. The post-travel PCR alone reduced the number of infectious days to 4851 (3714-7679), a reduction of 42% (35-49) compared with the base case.Interpretation: Routine asymptomatic testing for SARS-CoV-2 before travel can be an effective strategy to reduce passenger risk of infection during travel, although abbreviated quarantine with post-travel testing is probably needed to reduce population-level transmission due to importation of infection when travelling from a high to low incidence setting.Funding: University of California, San Francisco. [ABSTRACT FROM AUTHOR]

Locally tailored interventions for neglected tropical diseases (NTDs) are becoming increasingly important for ensuring that the World Health Organization (WHO) goals for control and elimination are reached. Mathematical models, such as those developed by the NTD Modelling Consortium, are able to offer recommendations on interventions but remain constrained by the data currently available. Data collection for NTDs needs to be strengthened as better data are required to indirectly inform transmission in an area. Addressing specific data needs will improve our modelling recommendations, enabling more accurate tailoring of interventions and assessment of their progress. In this collection, we discuss the data needs for several NTDs, specifically gambiense human African trypanosomiasis, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminths (STH), trachoma, and visceral leishmaniasis. Similarities in the data needs for these NTDs highlight the potential for integration across these diseases and where possible, a wider spectrum of diseases. [ABSTRACT FROM AUTHOR]

Background: With visceral leishmaniasis (VL) incidence at its lowest level since the 1960s, increasing attention has turned to early detection and investigation of outbreaks. Methods: Outbreak investigations were triggered by recognition of case clusters in the VL surveillance system established for the elimination program. Investigations included ascertainment of all VL cases by date of fever onset, household mapping and structured collection of risk factor data. Results: VL outbreaks were investigated in 13 villages in 10 blocks of 7 districts. Data were collected for 20,670 individuals, of whom 272 were diagnosed with VL between 2012 and 2019. Risk was significantly higher among 10–19 year-olds and adults 35 or older compared to children younger than 10 years. Outbreak confirmation triggered vector control activities and heightened surveillance. VL cases strongly clustered in tolas (hamlets within villages) in which > 66% of residents self-identified as scheduled caste or scheduled tribe (SC/ST); 79.8% of VL cases occurred in SC/ST tolas whereas only 24.2% of the population resided in them. Other significant risk factors included being an unskilled non-agricultural laborer, migration for work in a brick kiln, living in a kuccha (mud brick) house, household crowding, habitually sleeping outside or on the ground, and open defecation. Conclusions: Our data highlight the importance of sensitive surveillance with triggers for case cluster detection and rapid, careful outbreak investigations to better respond to ongoing and new transmission. The strong association with SC/ST tolas suggests that efforts should focus on enhanced surveillance in these disadvantaged communities. [ABSTRACT FROM AUTHOR]

Background On the Indian subcontinent, visceral leishmaniasis (VL) incidence is on track to reach elimination goals by 2020 in nearly all endemic districts. Although not included in official targets, previous data suggest post-kala-azar dermal leishmaniasis (PKDL) patients can act as an infection reservoir. Methods We conducted xenodiagnosis on 47 PKDL patients and 15 VL patients using laboratory-reared Phlebotomus argentipes. In direct xenodiagnosis, flies were allowed to feed on the patient's skin for 15 minutes. For indirect xenodiagnosis, flies were fed through a membrane on the patient's blood. Five days later, blood-fed flies were dissected and examined by microscopy and/or polymerase chain reaction (PCR). A 3-mm skin snip biopsy (PKDL) or venous blood (VL) was processed by quantitative PCR. Results Twenty-seven PKDL patients (57.4%) had positive results by direct and/or indirect xenodiagnosis. Direct was significantly more sensitive than indirect xenodiagnosis (55.3% vs 6.4%, P <.0001). Those with positive xenodiagnosis had median skin parasite loads >1 log10 unit higher than those with negative results (2.88 vs 1.66, P <.0001). In a multivariable model, parasite load, nodular lesions, and positive skin microscopy were significantly associated with positive xenodiagnosis. Blood parasite load was the strongest predictor for VL. Compared to VL, nodular PKDL was more likely and macular PKDL less likely to result in positive xenodiagnosis, but neither difference reached statistical significance. Conclusions Nodular and macular PKDL, and VL, can be infectious to sand flies. Active PKDL case detection and prompt treatment should be instituted and maintained as an integral part of VL control and elimination programs. [ABSTRACT FROM AUTHOR]

Background: Visceral Leishmaniasis (VL) is a neglected tropical disease that afflicts some of the poorest populations in the world including people living in the Bihar state of India. Due to efforts from local governments, NGOs and international organizations, the number of VL cases has declined in recent years. Despite this progress, the reservoir for transmission remains to be clearly defined since it is unknown what role post kala-azar dermal leishmaniasis (PKDL) and asymptomatic infections play in transmission. This information is vital to establish effective surveillance and monitoring to sustainably eliminate VL. Methodology/Principal Findings: We performed a longitudinal study over a 24-month period to examine VL transmission and seroconversion in households with VL, PKDL and asymptomatic infections in the Saran and Muzaffarpur districts of Bihar. During the initial screening of 5,144 people in 16 highly endemic villages, 195 cases of recently treated VL, 116 healthy rK39 positive cases and 31 PKDL cases were identified. Approximately half of the rK39-positive healthy cases identified during the initial 6-month screening period were from households (HHs) where a VL case had been identified. During the 18-month follow-up period, seroconversion of family members in the HHs with VL cases, PKDL cases, and rK39-positive individuals was similar to control HHs. Therefore, seroconversion was highest in HHs closest to the time of VL disease of a household member and there was no evidence of higher transmission in households with PKDL or healthy rK39-positive HHs. Moreover, within the PKDL HHs, (the initial 31 PKDL cases plus an additional 66 PKDL cases), there were no cases of VL identified during the initial screen or the 18-month follow-up. Notably, 23% of the PKDL cases had no prior history of VL suggesting that infection resulting directly in PKDL is more common than previously estimated. Conclusions/Significance: These observations argue that acute VL cases represent the major reservoir for transmission in these villages and early identification and treatment of VL cases should remain a priority for VL elimination. We were unable to obtain evidence that transmission occurs in HHs with a PKDL case. [ABSTRACT FROM AUTHOR]

Visceral Leishmaniasis (VL) is a neglected vector-borne disease. In India, it is transmitted to humans by Leishmania donovani-infected Phlebotomus argentipes sand flies. In 2005, VL was targeted for elimination by the governments of India, Nepal and Bangladesh by 2015. The elimination strategy consists of rapid case detection, treatment of VL cases and vector control using indoor residual spraying (IRS). However, to achieve sustained elimination of VL, an appropriate post elimination surveillance programme should be designed, and crucial knowledge gaps in vector bionomics, human infection and transmission need to be addressed. This review examines the outstanding knowledge gaps, specifically in the context of Bihar State, India. The knowledge gaps in vector bionomics that will be of immediate benefit to current control operations include better estimates of human biting rates and natural infection rates of P. argentipes, with L. donovani, and how these vary spatially, temporally and in response to IRS. The relative importance of indoor and outdoor transmission, and how P. argentipes disperse, are also unknown. With respect to human transmission it is important to use a range of diagnostic tools to distinguish individuals in endemic communities into those who: 1) are to going to progress to clinical VL, 2) are immune/refractory to infection and 3) have had past exposure to sand flies. It is crucial to keep in mind that close to elimination, and post-elimination, VL cases will become infrequent, so it is vital to define what the surveillance programme should target and how it should be designed to prevent resurgence. Therefore, a better understanding of the transmission dynamics of VL, in particular of how rates of infection in humans and sand flies vary as functions of each other, is required to guide VL elimination efforts and ensure sustained elimination in the Indian subcontinent. By collecting contemporary entomological and human data in the same geographical locations, more precise epidemiological models can be produced. The suite of data collected can also be used to inform the national programme if supplementary vector control tools, in addition to IRS, are required to address the issues of people sleeping outside. [ABSTRACT FROM AUTHOR]

Quantitative analysis and mathematical models are useful tools in informing strategies to control or eliminate disease. Currently, there is an urgent need to develop these tools to inform policy to achieve the 2020 goals for neglected tropical diseases (NTDs). In this paper we give an overview of a collection of novel model-based analyses which aim to address key questions on the dynamics of transmission and control of nine NTDs: Chagas disease, visceral leishmaniasis, human African trypanosomiasis, leprosy, soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis and trachoma. Several common themes resonate throughout these analyses, including: the importance of epidemiological setting on the success of interventions; targeting groups who are at highest risk of infection or re-infection; and reaching populations who are not accessing interventions and may act as a reservoir for infection,. The results also highlight the challenge of maintaining elimination 'as a public health problem' when true elimination is not reached. The models elucidate the factors that may be contributing most to persistence of disease and discuss the requirements for eventually achieving true elimination, if that is possible. Overall this collection presents new analyses to inform current control initiatives. These papers form a base from which further development of the models and more rigorous validation against a variety of datasets can help to give more detailed advice. At the moment, the models' predictions are being considered as the world prepares for a final push towards control or elimination of neglected tropical diseases by 2020. [ABSTRACT FROM AUTHOR]